Embracing a Data-Centric World: The Shift from Document Review to Data Review with Lineal
Written by Brian Stempel
“Intelligence is the ability to adapt to change.” – Stephen Hawking
The late-great Steven Hawking states the core defining characteristic of intelligence is the ability to change. Of course, he was talking about the most important kind of intelligence: human intelligence. In a world of GenAI promise and hype, we still value human intelligence above all others. This is as true in the Legal Industry as in any other profession. But what does it mean to adapt to change in today’s Legal landscape? We are experiencing a seismic shift in the nature and complexity of legal data and, in particular, data discovery. Understanding and embracing the transition from traditional electronic documents (and paper) to a data-centric worldview is critical to evolving your discovery practice.
Rethinking review methodologies and practices is essential to stay relevant and deliver results. This paradigm shift, emphasizing the extraction and analysis of data rather than just ‘looking at documents’, not only enhances the efficiency and accuracy of finding insights and setting strategy for individual matters but also provides strategic insights that transcend the specifics of individual matters and inform Practice Intelligence Analysis (PIA) systems.
The Traditional Document Review Model
Historically, legal teams have relied heavily on document review. Initially, this review was mostly paper-based and document-by-document. In time, Machine Learning and analytics tools were used to handle the sheer expanding volume of electronic documents that made document-by-document review ineffective and cost-prohibitive. This decade-old shift left what was considered the ‘Gold Standard’ of review (i.e. have a lawyer look at every document) behind by embracing Boolean keyword searching, DeNISTing, email threading, and eventually Technology Assisted Review (TAR) and the precision/recall rates and elusion tests that go with it.
However, the limitations of even the most technologically advanced document review become particularly evident when dealing with modern data types like chats, collaborative documents, hyperlinked content, non-textual documents like images and video, and ERP systems that can be dynamic and interconnected and do not easily fall into the “keywords plus TAR” paradigm.
The Rise of Data-Centric Review
A Data-centric review, in contrast, focuses on two essential differences from document review methodologies.
- Traditional electronic documents can be mined, reviewed and leveraged for future insights better when viewed through the lens of the data elements that make them important, than the document as a whole. For example, most keyword and TAR-based review involves reviewing results of keyword hits and the hit context within the document. Often, the context, not the full document, is all that is required to make a legal determination. Data-centric review allows for leveraging these decisions across an entire data set to speed up review and enhance TAR model training.
- Non-traditional documents simply are not documents anymore. Document requests and document productions are, or should be, quaintly antiquated terms. If you only request and produce “documents” today, you can’t comply with your legal obligations. Data, in the form of collaborative platform data, ERP data, non-textual data referenced above, plays an essential role.
- Traditional electronic documents can be mined, reviewed and leveraged for future insights better when viewed through the lens of the data elements that make them important, than the document as a whole. For example, most keyword and TAR-based review involves reviewing results of keyword hits and the hit context within the document. Often, the context, not the full document, is all that is required to make a legal determination. Data-centric review allows for leveraging these decisions across an entire data set to speed up review and enhance TAR model training.
Lineal’s Pioneering Data-Driven Methodologies
Lineal is at the forefront of this industry shift, employing data-centric methodologies that redefine how legal discovery is conducted. With Lineal’s award-winning platform, Amplify, and modules like ChatCraft, Images, Snippets, PrivFinder, BotDetector, Workflow, and Command Center fully integrated within Relativity, Lineal transforms data review processes, making them more efficient, transparent, and insightful.
With the pending release of Memory Bank, Lineal will further expand the Amplify platform and move the industry forward towards the reusability of data. Memory Bank allows legal teams to reuse data insights across matters, transforming legal spend into a reusable asset and significantly expediting case setups. With Memory Bank, the benefits of data-centric decisions within matters can be saved and reused across matters. Insights to matter elements such as privilege actors and associated privilege content, custodian collection history and collection decisions, workflow decisions and defensibility documentation, and associated budgetary implications can be reused for future insights as part of a Practice Intelligence Analysis system.
Leading the Industry into a Data-Centric World
Lineal’s commitment to a data-centric approach extends beyond just technological advancements. By participating in industry-leading discussions and developing whitepapers with other thought leaders, Lineal helps shape the future of legal discovery, emphasizing the importance of data over documents.
Lineal’s leadership in this area is clear. Through its advanced technologies and commitment to innovation, Lineal adapts to the changing landscape and sets new standards, leading the charge toward a more efficient and effective future in legal discovery.
About the Author
Brian Stempel is a law practice technology executive and thought leader with over 30 years of experience in delivering innovative solutions and services to the legal industry. He is the Senior Vice President of Strategic Client Solutions at Lineal where he helps clients solve legal challenges with Lineal’s award-winning Amplify platform. Before Lineal, Brian ran eDiscovery operations at Kirkland & Ellis, Paul Hastings, and Debevoise & Plimpton. A life-long learner he also holds executive education certificates from Cornell University, MIT Sloan School of Management, Columbia Business School, and Harvard Business School in various fields related to artificial intelligence, innovation, DEI, and leadership.
About Lineal
Lineal is an innovative eDiscovery and legal technology solutions company that empowers law firms and corporations with modern data management and review strategies. Established in 2009, Lineal specializes in comprehensive eDiscovery services, leveraging its proprietary technology suite, Amplify, to enhance efficiency and accuracy in handling large volumes of electronic data. With a global presence and a team of experienced professionals, Lineal is dedicated to delivering custom-tailored solutions that drive optimal legal outcomes for its clients. For more information, visit lineal.com